Tie-Breaking in Shortest Path Determination

ABSTRACT

A consistent tie-breaking decision between equal-cost shortest (lowest cost) paths is achieved by comparing an ordered set of node identifiers for each of a plurality of end-to-end paths. Alternatively, the same results can be achieved, on-the-fly, as a shortest path tree is constructed, by making a selection of an equal-cost path using the node identifiers of the diverging branches of the tree. Both variants allow a consistent selection to be made of equal-cost paths, regardless of where in the network the shortest paths are calculated. This ensures that traffic flow between any two nodes, in both the forward and reverse directions, will always follow the same path through the network.

FIELD OF THE INVENTION

This invention relates to consistently selecting paths among multiplepossibilities, such as equal-cost shortest paths, in a packet-forwardingcommunications network, such as an Ethernet network.

BACKGROUND TO THE INVENTION

In packet-forwarding communications networks, a node can learn about thetopology of the network and can decide, on the basis of the knowledge itacquires of the topology, how it will route traffic to each of the othernetwork nodes. The main basis for selecting a path is path cost, whichcan be specified in terms of a number of hops between nodes, or by someother metric such as bandwidth of links connecting nodes, or both. OpenShortest Path First (OSPF) and Intermediate System-to-IntermediateSystem (IS-IS) are widely used link-state protocols which establishshortest paths based on each node's advertisements of path cost. Theseprotocols typically do not attempt to tie-break between multiple,equal-cost, paths. Instead, they typically spread traffic across severalequal-cost paths. The spreading algorithms are not specified and canvary from router to router. Alternatively, they may make a localselection of a single path, but without consideration of consistencywith the selection made by other routers. Consequently, in either casethe reverse direction of a flow is not guaranteed to use the path usedby the forward direction.

Multicast routing protocols such as Multicast Open Shortest Path First(OSPF) depend on each router in a network constructing the same shortestpath tree. For this reason, MOSPF implements a tie-breaking scheme basedon link type, LAN vs. point-to-point, and router identifier to ensurethat identical trees are produced. However, basing the tie-breakingdecision on the parent with the largest identifier implies that, ingeneral, the paths used by the reverse flows will not be the same as thepaths used by the forward flows.

Spanning Tree Protocols (Spanning Tree Protocol (STP), Rapid SpanningTree Protocol (RSTP), Multiple Spanning Tree Protocol (STP) are ways ofcreating loop-free spanning trees in an arbitrary topology. The SpanningTree Protocol is performed by each node in the network. All of theSpanning Tree Protocols use a local tie-breaking decision based on(bridge identifier, port identifier) to select between equal-cost paths.In Spanning tree a root node is elected first, and then the tree isconstructed with respect to that root by all nodes. So, although allpaths are symmetrical for go and return traffic (by definition, a simpletree makes this the only possible construct), the election process isslow and the simple tree structure cannot use any redundant capacity.Similarly, Radia Perlman's Rbridges proposal uses the identifier of theparent node as tie-breaker.

Mick Seaman in his Shortest Path Bridging proposal to the EEE 802.1Working Group(http://www.ieee802.org/1/files/public/docs2005/new-seaman-shortest-path-0305-02.pdf)describes a simple protocol enhancement to the Rapid Spanning TreeProtocol which enforces consistent tie-breaking decisions, by adding a‘cut vector’. The proposal uses a VID per node, to identify a SpanningTree per node. In order to fit all the information that needs to betransmitted by a bridge in a single legal Ethernet frame, this techniquecurrently limits the size of the Ethernet network to 32 bridges.

FIG. 1 illustrates how, even for a trivial network example, atie-breaking method based on the parent node identifier fails to producesymmetric paths. In this example, the links are considered as havingequal-cost and so the determination of path cost simply considers thenumber of hops. Consider first computing the path from A to B. When thecomputation reaches node 2, the existence of equal-cost paths will bediscovered. There is a first path (A-1-3-6) and a second path (A-1-4-5).If the tie-breaking algorithm selects a path based on the parent nodewith the smallest identifier, it will select the second path (A-1-4-5)because node identifier 5 is smaller than node identifier 6. However,now consider computing the path from B to A. When the computationreaches node 1, the existence of equal-cost paths will be discovered.There is a first path (B-2-6-3) and a second path (B-2-5-4). Using thesame tie-breaking criterion, the tie-breaking algorithm selects thefirst path (B-2-6-3) because node identifier 3 is smaller than nodeidentifier 4. So, it can be seen that the shortest path computationsmade by nodes A and B provide inconsistent results.

There is a requirement in some emerging protocols, such as Provider LinkState Bridging (PLSB), a proposal to EEE 802.1aq, to preserve congruencyof forwarding across the network for both unicast and unknown/multicasttraffic and to use a common path in both forward and reverse directionsof flow. Accordingly, it is important that nodes can consistently arriveat the same decision when tie-breaking between equal-cost paths.Furthermore, it is desirable that a node can perform the tie-breakingwith the minimum amount of processing effort.

SUMMARY OF THE INVENTION

A first aspect of the invention provides a method of determiningforwarding information for use in forwarding packets at a first node ofa packet-forwarding network. The method determines the shortest pathsbetween the first node and a second node of the network and determineswhen a plurality of shortest paths have substantially equal-cost. Themethod forms, for each substantially equal-cost path, a set of nodeidentifiers which define the set of nodes in the path and then orderseach set of node identifiers using a first ordering criterion to form apath identifier. The first ordering criterion is independent of theorder in which node identifiers appear in the path. The method thenselects between the plurality of equal-cost paths by comparing the pathidentifiers. Each node of the network has a unique node identifier.

Advantageously, the first ordering criterion is increasing lexicographicorder or decreasing lexicographic order, although any ordering criterioncan be used which creates a totally ordered set of node identifiers.

Preferably, the method further comprises ordering the plurality of pathidentifiers into an ordered list using a second ordering criterion.Similarly, the second ordering criterion can be increasing lexicographicorder, decreasing lexicographic order or any ordering criterion whichcreates a totally ordered set of path identifiers.

Another aspect of the invention provides a method of determiningforwarding information for use in forwarding packets at a first node ofa packet-forwarding network. The method comprises determining shortestpaths between the first node and a second node of the network byiteratively forming a shortest path tree and determines, while formingthe shortest path tree, when a plurality of paths have equal-cost, eachequal-cost path comprising a branch which diverges from a divergencenode common to the equal-cost paths. The method identifies, in eachdiverging branch, a node identifier using a first selection criterion toform a branch identifier and selects between the plurality of branchesby comparing the branch identifiers.

Advantageously, the method uses a total ordering criterion to compareand select a node identifier in each branch, such as lexicographicorder.

Advantageously, the method records the node identifier which meets thefirst selection criterion in each of the diverging branches whilebacktracking to the divergence node. This has an advantage in furthersimplifying computation and reducing storage requirements.

Both aspects of the invention can be used to select two equal-cost pathsby using different first ordering/selection criteria and a common secondordering/selection criterion or by using a common first orderingcriterion/selection and different second ordering/selection criteria.Three or four equal-cost paths can be selected in a similar manner byconsistently applying the first and second ordering/selection criteriaat nodes and selecting identifiers at a particular position in theordered lists.

The invention can be used as a tie-breaker to select between equal-costpaths by comparing an ordered set of node identifiers for each of aplurality of end-to-end paths. Alternatively, it has been found that thesame results can be achieved, on-the-fly, as a shortest path tree isconstructed, by making a selection of an equal-cost path using the nodeidentifiers of the diverging branches of the tree, local to where theselection decision needs to be made. This has advantages of reducing theamount of computation, and reducing the amount of data which needs to bestored. Branches can be compared on a pair-wise basis to further reducethe amount of computation. This becomes particularly important as thesize and complexity of the network increases. Both variants of theinvention have the important property of allowing a consistent selectionto be made of equal-cost paths, regardless of where in the network theshortest paths are calculated. This ensures that traffic flow betweenany two nodes, in both the forward and reverse directions, will alwaysfollow the same path through the network.

The invention is not intended to be restricted to any particular way ofdetermining a shortest path: Dijkstra's algorithm, Floyd's algorithm, orany other suitable alternative can be used.

The invention can be used as a tie-breaker between equal-cost pathshaving exactly the same value, or paths which are within a desiredoffset of one another both in terms of link metric or number of hops.This may be desirable in real life situation to increase the diversitybetween the set of eligible paths. For example, it may not always becost-effective to deploy nodes and links in the symmetrical fashion ingeneral required to achieve exactly equal-cost between any twoend-points. By relaxing the constraint to requiring that the hop counton different routes be within one hop of each other, modest asymmetrycan still result in eligible routes, and loop-free topology is stillguaranteed because a difference of two hops is the minimum necessary toachieve a looping path.

It will be understood that the term “shortest path” is not limited todetermining paths based only on distance, and is intended to encompassany metric, or combination of metrics, which can be used to specify the“cost” of a link. A non-exhaustive list of metrics is: distance, numberof hops, capacity, speed, usage, availability.

The method is stable in the sense that the selection of an equal-costshortest path is not affected by the removal of parts of the networkthat are not on the selected paths, such as failed nodes or links.

Advantageously, the network is an Ethernet network although theinvention can be applied to other types of packet-forwarding networks,especially those that have a requirement for symmetrical traffic-routingpaths.

The functionality described here can be implemented in software,hardware or a combination of these. The invention can be implemented bymeans of a suitably programmed computer or any form of processingapparatus. Accordingly, another aspect of the invention providessoftware for implementing any of the described methods. The software maybe stored on an electronic memory device, hard disk, optical disk orother machine-readable storage medium. The software may be delivered asa computer program product on a machine-readable carrier or it may bedownloaded to a node via a network connection.

A further aspect of the invention provides a network node comprising aprocessor which is configured to perform any of the described methods.

A further aspect of the invention provides a network of nodes which eachconsistently apply the described methods to select between equal-costpaths.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention will be described, by way of example only,with reference to the accompanying drawings in which:

FIG. 1 shows a network topology having equal-cost paths;

FIG. 2 shows an example of a packet-forwarding network in which theinvention can be implemented;

FIG. 3 schematically shows apparatus at one of the bridging nodes ofFIG. 2;

FIG. 4 shows the locality of tie-breaking decisions;

FIGS. 5 to 7 show example network topologies for illustratingcalculation of shortest paths;

FIG. 8 shows a further example network topology for illustratingcalculation of shortest paths;

FIGS. 9 to 11 show tie-breaking steps of a shortest path calculation ofthe network topology shown in FIG. 8;

FIG. 12 shows an example of nodes dual-homed onto a mesh network;

FIGS. 13A and 13B illustrate properties of the tie-breaking method ofthe invention.

DESCRIPTION OF PREFERRED EMBODIMENTS

FIG. 2 shows an example of a link state protocol controlled Ethernetnetwork 10 in which the invention can be implemented and FIG. 3schematically shows apparatus at one of the nodes 41-48. Nodes (alsocalled bridges, or bridging nodes) 41-48 forming the mesh networkexchange link state advertisements 56 with one another. This is achievedvia the well understood mechanism of a link state routing system. Arouting system module 51 exchanges information 56 with peer nodes in thenetwork regarding the network topology using a link state routingprotocol. This exchange of information allows the nodes to generate asynchronized view of the network topology. At each node, a Shortest PathDetermination module 52 calculates a shortest path tree, whichdetermines the shortest path to each other node. The shortest pathsdetermined by module 52 are used to populate a Forwarding InformationBase 54 with entries for directing traffic through the network. As willbe described in greater detail below, situations will arise when module52 will encounter multiple equal-cost paths. A tie-breaking module 53selects one (or more) of the equal-cost paths in a consistent manner. Innormal operation, packets are received 57 at the node and a destinationlookup module 55 determines, using the FIB 54, the port (or multipleports in the case of multicast distribution) over which the receivedpacket should be forwarded 58. If there is not a valid entry in the FIB54 then the packet may then be discarded. It will be appreciated thatthe modules shown in FIG. 3 are for illustrative purposes only and maybe implemented by combining or distributing functions among the modulesof a node as would be understood by a person of skill in the art.

Various shortest path algorithms can be used to determine if a givennode is on the shortest path between a given pair of bridges. Anall-pairs shortest path algorithm such as Floyd's algorithm [R. Floyd:Algorithm 97 (shortest path), Communications of the ACM, 7:345, 1962] orDijkstra's single-source shortest path algorithm [E. W. Dijkstra: A noteon two problems in connection with graphs, Numerical Mathematics,1:269-271, 1959] can be implemented in the node 41-48 to compute theshortest path between pairs of nodes. It should be understood that anysuitable shortest path algorithm could also be utilized. The link metricused by the shortest path algorithm can be static or dynamicallymodified to take into account traffic engineering information. Forexample, the link metric can include a measure of cost such as capacity,speed, usage and availability.

By way of introduction to the problem, the requirements of atie-breaking algorithm which can make consistent decisions betweenequal-cost paths will firstly be described. The list of requirements isset out in Table 1 below:

TABLE 1 # Requirement Description 1 Complete The tie-breaking algorithmmust always be able to choose between two paths 2 Commutativetiebreak(a, b) = tiebreak(b, a) 3 Associative tiebreak(a, tiebreak(b,c)) = tiebreak(tiebreak(a, b), c) 4 Symmetric tiebreak(reverse(a),reverse(b)) = reverse(tiebreak(a, b)) 5 Local tiebreak(concat(a, c),concat(b, c)) = concat(tiebreak(a, b), c)The essence of a tie-breaking algorithm is to always ‘work’. No matterwhat set of paths the algorithm is presented with, the algorithm shouldalways be able to choose one and only one path. First and foremost, thetie-breaking algorithm should therefore be complete (1). For consistenttie-breaking, the algorithm must produce the same results regardless ofthe order in which equal-cost paths are discovered and tie-breaking isperformed. That is, the tie-breaking algorithm should be commutative (2)and associative (3). The requirement that tie-breaking between threepaths must produce the same results regardless of the order in whichpairs of paths are considered (3) is not so obvious and yet it isabsolutely necessary for consistent results as equal-cost paths arediscovered in a different order depending on the direction of thecomputation through the network. The tie-breaking algorithm must besymmetric (4), i.e. the tie-breaking algorithm must produce the sameresult regardless of the direction of the path: the shortest pathbetween two nodes A and B must be the reverse of the shortest pathbetween B and A. Finally, locality is a very important property ofshortest paths that is exploited by routing systems (5). The localityproperty simply says that: a sub-path of a shortest path is also ashortest path. This seemingly trivial property of shortest paths has animportant application in packet networks that use destination-basedforwarding. In these networks, the forwarding decision at intermediatenodes along a path is based solely on the destination address of thepacket, not its source address. Consequently, in order to generate itsforwarding information, a node needs only compute the shortest path fromitself to all the other nodes and the amount of forwarding informationproduced grows linearly, not quadratically, with the number of nodes inthe network. In order to enable destination-based forwarding, thetie-breaking algorithm must therefore preserve the locality property ofshortest paths: a sub-path of the shortest path selected by thetie-breaking algorithm must be the shortest path selected by thetie-breaking algorithm.

Considerations of computational efficiency put another seeminglydifferent requirement on the tie-breaking algorithm: the algorithmshould be able to make a tie-breaking decision as soon as equal-costpaths are discovered. FIG. 4 illustrates this point. An intermediatenode I is connected by two equal-cost paths, p and q, to node A and byanother pair of equal-cost paths, r and s, to node B. There aretherefore four equal-cost paths between nodes A and B, all going throughnode I: p+r, p+s, q+r, q+s. As the computation of the shortest path fromA to B progresses, the existence of equal-cost sub-paths between A and Iwill be discovered first. To avoid having to carry forward knowledge ofthese two paths, the tie-breaking algorithm should be able to choosebetween them as soon as the existence of the second equal-cost shortestsub-path is discovered. The tie-breaking decisions made at intermediatenodes will ultimately affect the outcome of the computation. Byeliminating one of the two sub-paths, p and q, between nodes A and I,the algorithm removes two of the four shortest paths between nodes A andB from further consideration. Similarly, in the reverse direction, thetie-breaking algorithm will choose between sub-paths r and s beforemaking a final determination. These local decisions must be consistentwith one another and, in particular, the choice between two equal-costpaths should remain the same if the paths were to be extended in thesame way. For instance, in the case depicted in FIG. 3, the tie-breakingalgorithm should verify the following four identities:

tiebreak(concat(p, r), concat(q, r))=concat(tiebreak(p, q), r)

tiebreak(concat(p, s), concat(q, s))=concat(tiebreak(p, q), s)

concat(p, tiebreak(r, s))=tiebreak(concat(p, r), concat(p, s))

concat(q, tiebreak(r, s))=tiebreak(concat(q, r), concat(q, s))

It turns out that the symmetry (4) and locality (5) conditions are bothnecessary and sufficient to guarantee that the tie-breaking algorithmwill make consistent local decisions, a fact that can be exploited toproduce very efficient implementations of the single-source shortestpath algorithm in the presence of equal-cost shortest paths.

The list of requirements set out in Table 1 is not intended to beexhaustive, and there are other properties of shortest paths that couldhave been included in Table 1. For example, if a link which is not partof a shortest path is removed from the graph, the shortest path is notaffected. Likewise, the tie-breaking algorithm's selection betweenmultiple equal-cost paths should not be affected if a link which is notpart of the selected path is removed from the graph, and that even ifthis link is part of some of the equal-cost paths that were rejected bythe algorithm.

A first embodiment of a consistent tie-breaking algorithm will now bedescribed. This algorithm begins by forming a path identifier for eachpath. The path identifier is an ordered list of the identifiers of eachnode traversed by the path through the network. The node identifiers aresorted in lexicographic order. The path identifier is the resultingconcatenation of the ordered node identifiers. FIG. 5 shows an examplenetwork, with end nodes A, B and intermediate nodes 0-9. A first path(along the top of FIG. 5) between nodes A and B traverses nodes havingthe node identifiers A-0-5-6-1-4-8-B. After ordering the list of nodeidentifiers in ascending lexicographic order, the path can berepresented by the path identifier 014568AB. This construction ensuresthat a path and its reverse will have the same path identifier.Furthermore, because the algorithm is only dealing with shortest pathsor nearly shortest paths, only two paths—the direct path and thecorresponding reverse path—can share an identifier. Finally, thetie-breaking algorithm simply selects the path with the smallest (orlargest) path identifier. The algorithm can be summarised as:

1) Sort the set of identifiers of the nodes in the path according to afirst ordering criterion which achieves a total ordering of the set ofnode identifiers. A preferred first ordering criterion is increasing ordecreasing lexicographic order;

2) Concatenate the set of ordered node identifiers to create a pathidentifier;

3) Sort the path identifiers according to a second ordering criterionwhich achieves a total ordering of the set of path identifiers. Apreferred second ordering criterion is increasing or decreasinglexicographic order;

4) Select the path whose path identifier appears at one end (first orlast) of the sorted set of path identifiers. Advantageously, this stepselects the path identifier appearing first in the ordered set of pathidentifiers.

Each node in the network that performs this algorithm consistently usesthe same ordering criteria and selects a path at the same agreedposition in the set of path identifiers, in order to select the samepath.

The term “lexicographic order” means the set of node identifiers arearranged in order of size of identifier. So, if node identifiers arealphabetic, the set of node identifiers are arranged in alphabetic orderA, B, C, D . . . etc.; if node identifiers are numerical, the set ofnode identifiers are arranged in numerical order. Clearly, this schemecan accommodate any way of labelling nodes, and any combination of typesof identifier. For example, a mix of numbers and letters could beordered by agreeing an order for numbers with respect to letters (e.g.order numbers first, then letters). Alternatively, each character can begiven it's American Standard Code for Information Interchange (ASCII)code and the ASCII codes can be sorted in increasing (decreasing) order.Each node uses the same convention to order the node identifiers ofpaths in the same manner. This algorithm will produce consistent resultsbecause: there is a one-to-one mapping between a path (strictly speakingbetween the pair made up of a path and its reverse) and its identifier,and there is a total ordering of the path identifiers.

Referring again to FIG. 5, the top path between nodes A and B isrepresented, after ordering, by the path identifier 014568AB. Similarly,a second path between nodes A and B traverses nodes A-0-7-9-1-4-8-B andthis can be represented, after ordering, by the path identifier014789AB. Finally, a third path (along the bottom of FIG. 5) betweennodes A and B traverses nodes A-0-7-9-2-3-8-B and this can berepresented, after ordering, by the path identifier 023789AB. Thetie-breaking algorithm compares each element of the ordered pathidentifier, in an agreed direction. In this example, the convention thatwill be used is that each node selects the lowest of the ordered pathidentifiers, when the path identifiers are compared in a particulardirection (e.g. left-to-right). The ordered path identifiers, for thethree equal-cost paths are:

-   -   014568AB    -   014789AB    -   023789AB        Starting with the left-hand element of the identifiers, all        three path identifiers begin with ‘0’. The next elements are ‘1’        or ‘2’, so only the top two identifiers need to be considered        any further. Reaching the fourth element, “0145 . . . ” is        smaller than “0147 . . . ” and so the top path is selected. Real        node identifiers in IS-IS and Ethernet are composed of six 8-bit        bytes and are usually written as a hexadecimal string such as:        00-e0-7b-c1-a8-c2. Nicknames of nodes can also be used,        providing they are used consistently.

FIG. 6 shows a simple network topology to illustrate the effects ofdifferent ordering criteria. Two nodes, X, Y, are connected by fourequal-cost paths having the node identifiers 1-8. Four possible optionswill now be described:

-   -   Sort node IDs by ascending order; sort path IDs by ascending        order; select first (smallest) path ID. If the node identifiers        in each path are ordered in ascending order of size (e.g. the        top path with nodes 1, 7 becomes 17), that gives the path        identifiers 17, 28, 35, 46. Arranging these path identifiers in        ascending order of size, and selecting the first path identifier        in the ordered list, has the result of selecting the first (top)        path, with the nodes 1 and 7.    -   Sort node IDs by ascending order; sort path IDs by ascending        order; select last (largest) path ID. This option has the result        of selecting the last (bottom) path, with the nodes 4 and 6.    -   Sort node IDs by descending order; sort path IDs by ascending        order; select first (smallest) path ID. Sorting the node        identifiers in each path in descending order of size gives path        identifiers (71, 82, 53, 64). Arranging these path identifiers        in ascending order of size gives (53, 64, 71, 82) and selecting        the first (smallest) path identifier in the ordered list, has        the result of selecting the third path, with the nodes 3 and 5.    -   Sort node IDs by descending order; sort path IDs by ascending        order; select last (largest) path ID. This option has the result        of selecting the second path, with the nodes 8 and 2.

As will be described in more detail below, there are situations in whichit is desirable for nodes to apply multiple, different, ordering and/orselection criteria to select multiple equal-cost paths.

So far this description assumes that the algorithm is non-local and thattie-breaking is performed after all the equal-cost paths have beenfound. However, it has been found that a local version of this algorithmcan produce the same results by considering only the nodes on thediverging branches. Indeed, the tie-breaking result depends only on therelative positions of the smallest node identifier in the divergingbranches. A second embodiment of a consistent tie-breaking algorithm canbe summarised as:

1) Find the node identifier in the diverging branch of the first pathwhich meets a first selection criterion. This can be considered a branchidentifier for the first path;

2) Find the node identifier in the diverging branch of the second pathwhich meets the first selection criterion. This can be considered abranch identifier for the second path;

3) Select one of the paths using a second selection criterion, whichoperates on the branch identifiers selected by steps (1) and (2).

Preferred options for the first selection criterion are to find the nodeidentifier which is the first (or last) when the node identifiers arearranged using a total ordering scheme, such as lexicographic order(increasing or decreasing lexicographic order). As will be explainedbelow, it is not necessary for the scheme to compile the total set ofnode identifiers in a branch and then order the set. Instead, the schemecan iteratively compare pairs of node identifiers using an awareness oflexicographic order. Similarly, preferred options for the secondselection criterion are to find the branch identifier which is the first(or last) when the branch identifiers are arranged using a totalordering scheme, such as lexicographic order (increasing or decreasinglexicographic order).

Referring again to the topology of FIG. 6, the four equal-cost pathsbetween nodes X and Y can represent four equal-cost diverging branchesfrom a parent node X. The tie-breaking algorithm needs to select one ofthe four branches. There are four possible options:

-   -   Identify the smallest node ID in each branch. This results in        (1, 2, 3, 4) as the branch identifiers. Then, identify the        smallest of the branch identifiers. This has the result of        selecting the first (top) path, with the nodes 1 and 7. Identify        the smallest node ID in each branch. Then, identify the largest        of the branch identifiers. This option has the result of        selecting the last (bottom) path, with the nodes 4 and 6.    -   Identify the largest node ID in each branch. This results in (5,        6, 7, 8) as the branch identifiers. Then, identify the smallest        of the branch identifiers. This has the result of selecting the        path with the nodes 3 and 5.    -   Identify the largest node ID in each branch. Then, identify the        largest of the branch identifiers. This option has the result of        selecting the path with the nodes 2 and 8.

As will be described in more detail below, there are situations in whichit is desirable for nodes to apply multiple, different, ordering and/orselection criteria to select multiple equal-cost paths.

This algorithm can be implemented very easily and efficiently withsimple comparisons. FIG. 7 shows another network topology. The localversion of the method, will start at node 13, and proceed to find twodiverging branches leading from node 15. The method explores the twoseparate paths as far as node 16, where the two paths converge again. Atthis point, the method examines the node identifiers for each of the twobranches. For the first branch, the node identifiers are: 10, 14, 17, 21and for the second branch the node identifiers are: 11, 12, 19, 20. Thebranch with the lowest identifier (10) is part of the top path. Themethod can simply backtrack from node 16 towards node 15, keeping trackof the lowest node identifier found in each branch. At each backwardstep, the method compares the lowest node identifier found so far, withthe new node identifier encountered at that step. The lowest nodeidentifier is stored. When the method has backtracked as far as node 15,the two lowest values (10 in the top branch, 11 in the lower branch) cansimply be compared to one another to find the branch having the lowestnode identifier. Accordingly, the top branch, which forms part of thetop path, is selected. The part of the path common to both of thediverging branches is ignored when performing this tie-breaking.

One of the most common algorithms for finding shortest cost paths in anetwork is Dijkstra's algorithm [Dijkstra 59]. It solves the problem offinding the shortest paths from a point in a graph (the source or rootnode) to all possible destinations when the length of a path is definedas the sum of the positive hop-by-hop link costs. This problem issometimes called the single-source shortest paths problem. For a graph,G=(N, L) where N is a set of nodes and L is a set of links connectingthem, Dijkstra's algorithm uses a priority queue, usually called TENT,to visit the nodes in order of increasing distance from the source node.The other data structures needed to implement Dijkstra's algorithm are:

Distance: an array of best estimates of the shortest distance from thesource node to each node

Parent: an array of predecessors for each node

The following text describes the known Dijkstra's algorithm, anddescribes how it can be modified to perform a tie-break when multipleequal-cost paths are discovered. Dijkstra's algorithm is described herebecause it is one of the most commonly used shortest path findingalgorithms. However, it will be appreciated that other algorithms couldequally be used. The initialization phase sets the Distance of eachnode, except the source node itself, to Infinity. The Distance of thesource node is set to zero and its Parent is set to Null as it is theroot of the tree. At the start of the computation, the priority queuecontains only the source node. As the algorithm progresses, nodes areadded to the priority queue when a path from the source node to them isfound. Nodes are pulled out of the priority queue in order of increasingdistance from the source node, after the shortest path between them andthe source node has been found. The algorithm stops when all the nodesreachable from the source node have been cycled through the priorityqueue. While the priority queue TENT is not empty, the algorithmperforms the following steps:

1) Find the node N in TENT which is closest to the source node andremove it from TENT

2) For each node connected to N, if the node's distance to the sourcewould be reduced by making N its parent, then change the node's parentto N, set the node's distance to the new distance, and add the node toTENT.

Upon completion of the algorithm, Distance(node) contains the shortestdistance from the source node to the node (or Infinity if the node isnot reachable from the source node) and Parent(node) contains thepredecessor of the node in the spanning tree (except for the source nodeand the nodes which are not reachable from the source node). The parentof a node is updated only if changing parents actually reduces thenode's distance. This means that, if multiple equal-cost shortest pathsexist between the source node and some other node, only the first oneencountered during the execution of the algorithm will be considered.The above steps are conventional steps of Dijkstra's algorithm. At thispoint Dijkstra is modified to add a consistent tie-breaking step. Step 2above is modified as follows:

2) For each node connected to node N do the following:

2a) if the node's distance to the source would be reduced by making Nits parent, then change the node's parent to N, set the node's distanceto the new distance, and add the node to TENT.

2b) if the node's distance to the source node would remain the sameafter making N its parent, then invoke the tie-breaking algorithm todetermine if the node's parent should be changed.

The tie-breaking algorithm is invoked when a convergence point of twodiverging branches is reached. For example, considering the topologyshown in FIG. 7, if Dijkstra's algorithm is started from node 13,diverging branches are discovered leading from node 15 (an upper branchwith nodes 10, 14, 17, 21 and a lower branch with nodes 11, 12, 19, 20)and these diverging branches converge at node 16. It is at node 16 thatthe tie-breaking algorithm would be invoked to select between the twobranches.

The pseudo-code below shows an implementation of the modified Dikstra'salgorithm with consistent tie-breaking using a priority queueimplementation of the TENT set. The Enqueue operation takes twoarguments, a queue and a node, and puts the node in the proper queueposition according to its distance from the source node. The Dequeueoperation removes from the queue the node at the head of the queue i.e.the node with the smallest distance from the source node.

for each Node in Network do Distance(Node) = Infinity; Empty(Tent);Distance(Source) = 0; Parent(Source) = Null; Node = Source; do   foreach Link in OutgoingLinks(Node) do     newDistance = Distance(Node) +Cost(Link);     Child = EndNode(Link);     if (newDistance <Distance(Child) do       Distance(Child) = newDistance;      Parent(Child) = Node;       Enqueue(Tent, Child);     else if(newDistance == Distance(Child) do       Parent(Child) = TieBreak(Node,Parent(Child)); while (Node = Dequeue(Tent));The tie-breaking algorithm operates by back-tracking the two equal-costpaths, starting from the current parent and the new candidate parent ofthe node respectively, all the way back to the divergence point. Thefact that the two diverging paths may have a different number of hopscomplicates matters slightly as the two paths must be backtracked by anunknown, un-equal number of hops. This problem can be resolved by alwaysback-tracking the longer of the two paths first or both simultaneouslywhen they have equal-cost. Alternatively, this difficulty can beeliminated altogether by ensuring that two paths will only be consideredto be of equal-cost if, and only if, they have the same number of hops.This is easily accomplished by either incorporating a hop count in thepath cost or by using the hop count as a first order tie-breaker.

The following pseudo-code shows an implementation of the tie-breakingalgorithm that assumes that the two paths have the same number of hops(and therefore so do their diverging branches). The tie-breakingfunction takes the two nodes at the end of two equal paths and returnsone of them to indicate which of the two paths it selected.

old = oldParent; new = newParent; oldMinId = SysId(old); newMinId =SysId(new); while ((old=Parent(old)) != (new=Parent(new))) do   tmp =SysId(old);   if (tmp < oldMinId) do oldMinId = tmp;   tmp = SysId(new);  if (tmp < newMinId) do newMinId = tmp; if (newMinId < oldMinId) returnnewParent; else return oldParent;The frequency with which the algorithm needs to be performed depends onthe application. PLSB essentially needs to compute the all-pairsshortest paths (sometimes a subset thereof). In this case Dijkstra'salgorithm needs to be run for all the nodes in the network (all but oneto be precise). Floyd's algorithm computes the all-pairs shortest pathsso it would need to be run only once. Other applications may onlyrequire the computation of a smaller number of paths (e.g. if only oneshortest path is required then Dijkstra's algorithm would have to be runonly once with one of the path's endpoints as the source).

FIG. 8 shows an example network of nodes A-H, J interconnected by links.For each link, a metric associated with that link is shown as an integervalue on the link. There are six different, equal-cost, shortest pathsbetween node A and node B in this network. These are shown in the tablebelow with their respective length and path identifier:

Path AGDHB AGCHB AGCJB AFCHB AFCJB AFEJB Length 10 10 10 10 10 10Identifier ABDGH ABCGH ABCGJ ABCFH ABCFJ ABEFJ

All of these six paths have the same length, 10. The non-local versionof the tie-breaking algorithm will select the one with the smallest pathidentifier (ABCFH), i.e. path AFCHB. The remainder of this section showshow the local version of the tie-breaking algorithm arrives at the sameresult by making only local tie-breaking decisions as equal-cost pathsand sub-paths are discovered during the execution of Dijkstra'salgorithm. Dijsktra's algorithm initializes a table of distances andparents (or predecessors) for the nodes in the network. All thedistances are initially set to infinity except for the source node whosedistance is set to zero. The parents are undefined at this stage:

Node A B C D E F G H J Distance 0 ∞ ∞ ∞ ∞ ∞ ∞ ∞ ∞ Parent — — — — — — — ——Dijkstra's algorithm also initializes its priority queue to contain onlythe source node, A: TENT=[(A, 0)].The first iteration of the Dijkstra loop selects the first and only nodein TENT, node A. Then for each of node A's neighbours, namely nodes Fand G, it updates their distance to the source and makes node A theirparent. Finally these two nodes are added to the TENT priority queue.During this first iteration of Dijkstra's algorithm the table ofdistances and parents becomes:

Node A B C D E F G H J Distance 0 ∞ ∞ ∞ ∞ 2 1 ∞ ∞ Parent — — — — — A A ——At the end of this first iteration the priority queue is: TENT=[(G, 1),(F, 2)]. The second iteration of the Dijkstra loop removes the node withthe smallest distance, node G, from the priority queue. It updates twoof G's neighbours that have not been processed yet, nodes C and D, andadds them to the priority queue:

Node A B C D E F G H J Distance 0 ∞ 5 4 ∞ 2 1 ∞ ∞ Parent — — G G — A A ——At the end of the second iteration, the priority queue is: TENT=[(F, 2),(D, 4), (C, 5)]. The third iteration of the Dijkstra loop removes node Ffrom the priority queue. It updates two neighbours of node F, nodes Cand E, and adds node E to the priority queue (node C is there already).The distance of node C does not change but there is a new candidateequal path between node A and node C going through node F. Thetie-breaking algorithm must therefore be invoked to choose between thisnew path going through node F and the old one going through node G. Thisis shown in FIG. 9. The tie-breaking algorithm is invoked with the newcandidate parent of node C, node F, and its old parent, node G. oldMinis set to the identifier of the old parent, G, and newMin is set to theidentifier of the new parent, F. Because nodes F and G share the sameparent (node A), the backtracking loop is not executed. The tiebreakingsimply compares oldMin and newMin and because newMin=F<G=oldMin, node Fis selected as the new parent of node C:

Node A B C D E F G H J Distance 0 ∞ 5 4 4 2 1 ∞ ∞ Parent — — F G F A A ——At the end of the third iteration, the priority queue is: TENT=[(D, 4),(E, 4), (C, 5)]. The fourth iteration of the Dijkstra loop removes oneof the two nodes with distance 4, node D for instance, from the priorityqueue. Of D's two neighbours only one, node H, is updated and added tothe priority queue:

Node A B C D E F G H J Distance 0 ∞ 5 4 4 2 1 6 ∞ Parent — — F G F A A D—At the end of the fourth iteration, the priority queue is: TENT=[(E, 4),(C, 5), (H, 6)]. The fifth iteration of the Dijkstra loop removes node Efrom the priority queue. Of E's two neighbours only one, node J, isupdated and added to the priority queue.

Node A B C D E F G H J Distance 0 ∞ 5 4 4 2 1 6 6 Parent — — F G F A A DEAt the end of the fifth iteration, the priority queue is: TENT [(C, 5),(H, 6), (J, 6)].The sixth iteration of the Dijkstra's loop removes node C from thepriority queue. Two of C's neighbours, nodes J and H, have equal-costpaths to node A through node C. The tie-breaking algorithm musttherefore be invoked twice for nodes J and H respectively. For node J,the tie-breaking algorithm is invoked with the new potential parent,node C, and the old parent, node E. oldMin is set to the identifier ofthe old parent, E, and newMin is set to the identifier of the newparent, C. Because these two nodes, E and C, share the same parent (nodeF), the backtracking loop is not executed. The tiebreaking simplycompares oldMin and newMin and because newMin=C<E=oldMin, the new parentis selected. Node J's parent is therefore replaced by node C. This isshown in FIG. 10. For node H, the tie-breaking algorithm is invoked withthe new potential parent, node C, and the old parent, node D. oldMin isset to the identifier of the old parent, D, and newMin is set to theidentifier of the new parent, C. Because these two nodes have differentparents, both paths must be backtracked one hop further. D's parent is Gand because G>oldMin (=D), oldMin does not change. C's parent is F andbecause F>newMin (=C), newMin does not change either. Because F and Gshare the same parent, node A, the backtracking loop stops. Thetiebreaking algorithm then compares oldMin and newMin and becausenewMin=C<D=oldMin, node C is selected to become node H's new parent.This is shown in FIG. 11.

Node A B C D E F G H J Distance 0 ∞ 5 4 4 2 1 6 6 Parent — — F G F A A CCAt the end of the sixth iteration, the priority queue is: TENT=[(H, 6),(J, 6)]. The seventh iteration of the Dijkstra's loop removes one of thetwo nodes with distance 6, node H for instance, from the priority queue.Only one of H's neighbours, node B, is updated and added to the priorityqueue:

Node A B C D E F G H J Distance 0 10 5 4 4 2 1 6 6 Parent — H F G F A AC CAt the end of the seventh iteration, the priority queue is: TENT=[(J,6), (B, 10)].The eighth iteration of the Dijkstra's loop removes node J from thepriority queue. Of J's neighbours, only node B needs to be updated. Itsdistance does not change but there is a new candidate equal path betweennode A and node B going through node J.The tie-breaking algorithm is invoked with the new potential parent ofnode B, node J, and the old parent, node H. oldMin is set to theidentifier of the old parent, H, and newMin is set to the identifier ofthe new parent, J. Because these two nodes, H and J, share the sameparent (node C), the backtracking loop is not executed. The tiebreakingsimply compares oldMin and newMin and because oldMin=H<J=newMin, the oldparent is selected and node B's parent remains the same.

Node A B C D E F G H J Distance 0 10 5 4 4 2 1 6 6 Parent — H F G F A AC CAt the end of the eighth iteration, the priority queue is: TENT=[(B,10)]. Finally the last iteration of the Dijkstra's loop removes node Bfrom the queue and the algorithm terminates because none of B'sneighbours can be updated (node B is the node that is the furthest awayfrom the source node A).The reverse of the shortest path from node A to node B can be readdirectly from the parent table starting at node B and following theparents until node A is reached: BHCFA. The shortest path from node A tonode B selected by the local tie-breaking algorithm is therefore itsreverse path: AFCHB.Although there are 6 equal-cost paths between nodes A and B, the localtie-breaking was only invoked a total of 4 times during the execution ofDijkstra's algorithm. At its first invocation, the tie-breakingalgorithm had to choose between sub-paths AFC and AGC. It selectedsub-path AFC, thereby eliminating two paths, AGCJB and AGCHB, fromfurther consideration. At its second invocation, the tie-breakingalgorithm had to choose between sub-paths AFCJ and AFEJ. It selectedsub-path AFCJ, thereby eliminating a third path, AFEJB, from furtherconsideration. At its third invocation, the tie-breaking algorithm hadto choose between sub-paths AGDH and AGCH. It selected sub-path AGCH,thereby eliminating a fourth path, AGDHB, from further consideration.Finally, at its fourth invocation, the tie-breaking algorithm had tochoose between paths AFCHB and AFCJB. It eliminated a fifth path, AFCJB,and selected path AFCHB as the final solution.

Selection of Equal-Cost Multi-Paths for Load Spreading

In many networking applications it is often advantageous to use severalequal-cost paths, especially if this can be achieved in a consistentfashion. By using two variants of the tie-breaking algorithm, it ispossible to use two equal-cost paths between a pair of nodes when theyexist. FIG. 12 shows a common networking scenario in which edge nodes Xand Y are each dual-homed on a full mesh of core nodes A, B, C, D. Forredundancy, each edge node is connected to two core nodes, with node Xconnected to core nodes A and B and node Y connected to nodes C and D.Each core node is connected to all of the other core nodes, e.g. node Ais connected to B, C, and D. The problem with this topology is that ifonly one shortest path is used between a pair of nodes, a lot of accesscapacity will be wasted under normal circumstances. When multipleequal-cost shortest paths exist between two nodes, two variants of thetie-breaking algorithm can be used to consistently select exactly twopaths. Any convention, agreed by all nodes, can be used to make theselection between equal-cost paths. One particularly convenientconvention is to select a first path having the smallest identifier anda second path having the largest identifier. In FIG. 12, since the corenodes are fully meshed, four equal-cost paths exist between the edgenodes X and Y: (X, A, C, Y), (X, A, D, Y), (X, B, C, Y), (X, B, D, Y).The two variants of the tie-breaking algorithm will select these twopaths:

-   -   (X, min(A, B), min(C, D), Y) and,    -   (X, max(A, B), max(C, D), Y).        Because the node identifiers are unique, min(A, B) !=max(A, B)        and min(C, D) !=max(C, D): these two paths are maximally        diverse: they have only their endpoints in common. In FIG. 12,        the two selected paths are path (X, A, C, Y) and path (X, B, D,        Y).

One of the important properties of the tie-breaking method describedabove is that a change to the network which does not affect one of theset of paths for which the tie-break needs to decide between has noimpact on the outcome of the tie-break. Such changes may involve removalof parts of the network that are not on the selected paths, such asfailed nodes or links. Another important property is that when multiplepaths equal-cost paths are used, a failure in one path does not affectthe stability of the others. Similarly, the addition of a link will onlyaffect one of the equal cost paths, not both. This is important forstability of the network.

FIGS. 13A and 13B illustrate other important properties of thetie-breaking method of the present invention:

-   -   a single failure in the presence of equal-cost paths cannot        force a loop;    -   a failure cannot both close the loop and shift the point of        attachment of the root;    -   a failure cannot produce a shorter path;

the tie-breaking algorithm prevents ranking of equal-cost paths fromchanging the shortest path.

FIGS. 13A and 13B illustrate these properties with a simple networktopology having nodes A, B, C, D and R. Considering FIG. 13A, theshortest path between R and a set of nodes A-D uses a link R-A. There isa choice of two equal-cost branches to reach node C from Node A. Usingone of the tie-breaking methods described above, the branch A-B-C isconsistently selected rather than the branch A-D-C. Similarly, in thereverse direction, the link C-B-A is consistently selected instead ofC-D-A. FIG. 13B shows a situation, at a later point in time, when thelink R-A has failed. Node R now connects to the set of nodes A-D via thenext best link, R-C. There is a choice of two equal-cost branches toreach node A from Node C. Again, the branch C-B-A is consistentlyselected rather than the branch C-D-A. Without the use of thisconsistent tie-breaking algorithm, a loop A-B-C-D-A could arisefollowing the failure in link R-A, with nodes A and B being slow andpromiscuous in their behaviour and nodes C and D being agile. Thisproperty is particularly useful to guarantee loop freeness for multicastforwarding.

The invention is not limited to the embodiments described herein, whichmay be modified or varied without departing from the scope of theinvention.

1. A method of determining forwarding information for use in forwarding packets at a first node of a packet-forwarding network, each node of the network having a unique node identifier, the method comprising: determining shortest paths between the first node and a second node of the network; determining when a plurality of shortest paths have substantially equal-cost; forming, for each substantially equal-cost path, a set of node identifiers which define the set of nodes in the path; ordering each set of node identifiers using a first ordering criterion to form a path identifier, wherein the first ordering criterion is independent of the order in which node identifiers appear in the path; selecting between the plurality of equal-cost paths by comparing the path identifiers.
 2. A method according to claim 1 where the step of determining when a plurality of shortest paths have substantially equal-cost is replaced with determining when a plurality of shortest paths have exactly equal-cost.
 3. A method according to claim 1 wherein the first ordering criterion creates a totally ordered set of node identifiers.
 4. A method according to claim 1 wherein the first ordering criterion is one of: increasing lexicographic order, decreasing lexicographic order.
 5. A method according to claim 1 further comprising ordering the plurality of path identifiers into an ordered list using a second ordering criterion.
 6. A method according to claim 5 wherein the second ordering criterion creates a totally ordered set of path identifiers; and, the step of selecting between the plurality of equal-cost paths comprises selecting the equal-cost path that appears at one end of the ordered list of path identifiers.
 7. A method according to claim 6 wherein the step of selecting between a plurality of equal-cost paths comprises selecting the equal-cost path that appears one of: first in the ordered list of path identifiers; last in the ordered list of path identifiers.
 8. A method according to claim 5 wherein the second ordering criterion is one of: increasing lexicographic order, decreasing lexicographic order.
 9. A method according to claim 5 further comprising selecting two of the substantially equal-cost paths by at least one of: using different first ordering criteria and a common second ordering criterion; using a common first ordering criterion and different second ordering criteria.
 10. A method according to claim 5 further comprising selecting four of the substantially equal-cost paths by: using two different first ordering criteria and a common second ordering criterion; using the same two first ordering criteria and a different second ordering criterion.
 11. A method according to claim 9 wherein the first ordering criteria are: increasing lexicographic order, decreasing lexicographic order; and the second ordering criteria are: increasing lexicographic order, decreasing lexicographic order.
 12. A method of determining forwarding information for use in forwarding packets at a first node of a packet-forwarding network, each node of the network having a unique node identifier, the method comprising: determining shortest paths between the first node and a second node of the network by iteratively forming a shortest path tree; determining, while forming the shortest path tree, when a plurality of paths have equal-cost, each equal-cost path comprising a branch which diverges from a divergence node common to the equal-cost paths; identifying, in each diverging branch, a node identifier using a first selection criterion to form a branch identifier; selecting between the plurality of branches by comparing the branch identifiers.
 13. A method according to claim 12 wherein the first selection criterion uses a total ordering criterion to compare and select a node identifier in each branch.
 14. A method according to claim 12 wherein the first selection criterion uses lexicographic order to compare and select a node identifier in each branch.
 15. A method according to claim 14 wherein the first selection criterion uses lexicographic order to select one of: a node identifier appearing first in lexicographic order; a node identifier appearing last in lexicographic order.
 16. A method according to claim 12 further comprising recording the node identifier which meets the first selection criterion in each of the diverging branches while backtracking to the divergence node.
 17. A method according to claim 16 further comprising, at each backwards step, comparing the recorded node identifier with a new node identifier encountered at that step and recording the node identifier which meets the first selection criterion.
 18. A method according to claim 12 further comprising selecting between the plurality of branches by selecting a branch identifier using a second selection criterion.
 19. A method according to claim 18 wherein the second selection criterion uses a total ordering criterion to compare and select the branch identifiers.
 20. A method according to claim 19 wherein the second selection criterion uses lexicographic order to select a branch identifier.
 21. A method according to claim 20 wherein the second selection criterion uses lexicographic order to select one of: a node identifier appearing first in lexicographic order; a node identifier appearing last in lexicographic order.
 22. A method according to claim 12 which selects between the plurality of branches on a pair-wise basis.
 23. A method according to claim 18 further comprising selecting two of the equal-cost paths by at least one of: using different first selection criteria and a common second selection criterion; using a common first selection criterion and different second selection criteria.
 24. A method according to claim 18 further comprising selecting four of the equal-cost paths by: using two different first selection criteria and a common second selection criterion; using the same two first selection criteria and a different second selection criterion.
 25. A method according to claim 23 wherein the first selection criteria are: largest node identifier; smallest node identifier; and the second selection criteria are largest branch identifier; smallest branch identifier.
 26. A method according to claim 12 comprising using Dijkstra's algorithm to iteratively form a shortest path tree.
 27. A computer program product comprising a machine-readable medium bearing instructions which, when executed by a processor, cause the processor to implement the method of claim
 1. 28. A network node comprising a processor which is configured to perform the method of claim
 1. 29. A network of nodes which each consistently apply the method according to claim 1 to select between equal-cost paths.
 30. A computer program product comprising a machine-readable medium bearing instructions which, when executed by a processor, cause the processor to implement the method of claim
 12. 31. A network node comprising a processor which is configured to perform the method of claim
 12. 32. A network of nodes which each consistently apply the method according to claim 12 to select between equal-cost paths. 